The idea behind this project was to create a concise data analysis in the energy domain that could showcase my ability to extract insights and narrate a compelling story. The focus is on exploring the relationship between CO₂ emissions, economic well-being, and the type of energy used to generate electricity across different regions of the world over various time periods.
The visual narrative was designed as a step-by-step journey:
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Global CO₂ Trend (Scatterplot)
The story begins by showing the global temporal trend of CO₂ emissions. Over the last 50 years, emissions have grown significantly, which is highlighted through a scatterplot. -
1974 vs 2024 Emissions (Barplot)
Next, the narrative compares emissions between 1974 and 2024. A barplot illustrates which continents have increased their emissions and which have managed to reduce them. -
Emissions vs Economic Growth (Scatterplot)
Since fossil fuels often drive faster economic growth compared to renewables, the question arises: is there a trade-off in terms of wealth when choosing renewables?
To explore this, a scatterplot correlates total emissions with GDP per capita, first at the continental level and then in more detail by geographic area. This visualization demonstrates that regions relying on renewables can still achieve positive economic well-being. -
Ranking Renewable Usage (Horizontal Barplot)
The narrative continues with a horizontal bar chart ranking regions by their share of renewable energy usage, offering a clear comparative view. -
Asia vs Europe Energy Mix (Pie Chart)
Finally, the story concludes with a pie chart comparing the electricity generation sources in Asia and Europe, highlighting the differences in energy mix.
Throughout the project, I applied a range of data analysis and visualization skills:
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Data Processing & Cleaning
- Used pandas and numpy to filter, clean, and aggregate datasets.
- Used pandasql to perform some queries and show my abilites in SQL.
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Data Visualization
- Created interactive and didactic visualizations using Plotly.
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AI-Assisted Attributes
- Disclaimer: For certain graphical attributes, I used AI to identify key parameters. However, the overall work was consciously designed and executed by me, ensuring that AI was used responsibly and purposefully.
The datasets used in this project come from trusted sources and were integrated to maintain coherence in both narrative and visualization:
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Country Codes Dataset
ISO-3166 Country Codes -
Annual CO₂ Emissions per Country (OWID)
Annual CO₂ Emissions Dataset -
GDP per Capita (World Bank via OWID)
GDP per Capita Dataset -
Electricity Generation by Source (OWID)
Electricity Generation by Source Dataset
These datasets were carefully selected and combined to ensure a coherent and impactful storytelling experience.